Evaluating holistic socio-environmental impact of digital health: scoping review of decision-making frameworks
Sara Consilia Papavero et al.
Abstract
Purpose The 2030 Agenda highlights the transformative role of digital technologies in advancing human progress, reducing inequalities and promoting sustainable knowledge societies. Digital Health (DH) enhances healthcare effectiveness, resilience and equity, while addressing environmental and climate challenges. To fill a literature gap, we conducted a scoping review of methodologies for DH impact assessment, focusing on social and environmental dimensions aligned with the six aims of Value-Based Health Care (VBHC). Design/methodology/approach The review followed JBI methodology and PRISMA-ScR guidelines. PubMed, Scopus and Cochrane searches (2014–2024, English) retrieved studies addressing at least three domains of the Sextuple Aim: Experience of Care, Population Health, Reduced Cost, Care Team Well-Being, Health Equity, and Environmental Impact. Findings From 8,243 records, 53 studies met criteria. None addressed all six aims. Experience of Care (98.11%) and Population Health (94.34%) dominated assessments, whereas Environmental Impact appeared in 11.32%. Thematic analysis yielded 128 items across 10 domains, 26 topics, and 92 issues. Experience of Care, notably user engagement and process costs, was most developed. Environmental Impact remained limited to carbon footprint and transparency. Social implications By highlighting key gaps, the review supports balanced, evidence-based DH decision-making and helps stakeholders prioritize innovations delivering technical, social and environmental value. Originality/value This is the first systematic mapping of DH's social and environmental evaluation within the Sextuple Aim, resulting in a Holistic Impact Framework integrating underrepresented dimensions.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.